Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines
Annals of Mathematics and Artificial Intelligence
The meta-elliptical distributions with given marginals
Journal of Multivariate Analysis
Tail dependence functions and vine copulas
Journal of Multivariate Analysis
On the simplified pair-copula construction - Simply useful or too simplistic?
Journal of Multivariate Analysis
D-vine EDA: a new estimation of distribution algorithm based on regular vines
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Efficiently sampling nested Archimedean copulas
Computational Statistics & Data Analysis
An Introduction to Copulas
Bayesian spatial modeling and interpolation using copulas
Computers & Geosciences
Vine copulas with asymmetric tail dependence and applications to financial return data
Computational Statistics & Data Analysis
Factor copula models for multivariate data
Journal of Multivariate Analysis
Estimating standard errors in regular vine copula models
Computational Statistics
Hi-index | 0.03 |
Regular vine distributions which constitute a flexible class of multivariate dependence models are discussed. Since multivariate copulae constructed through pair-copula decompositions were introduced to the statistical community, interest in these models has been growing steadily and they are finding successful applications in various fields. Research so far has however been concentrating on so-called canonical and D-vine copulae, which are more restrictive cases of regular vine copulae. It is shown how to evaluate the density of arbitrary regular vine specifications. This opens the vine copula methodology to the flexible modeling of complex dependencies even in larger dimensions. In this regard, a new automated model selection and estimation technique based on graph theoretical considerations is presented. This comprehensive search strategy is evaluated in a large simulation study and applied to a 16-dimensional financial data set of international equity, fixed income and commodity indices which were observed over the last decade, in particular during the recent financial crisis. The analysis provides economically well interpretable results and interesting insights into the dependence structure among these indices.